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Suppose you want to build an efficient natural language generation system that can generate a summary given an article. List any possible techniques and tools you may use. Output:
assistant
Some techniques and tools that could be used to build an efficient natural language generation system include the use of text representation models such as Word Embeddings (e.g. GloVe), language models such as Recurrent Neural Networks (RNN), Long Short-Term Memory (LSTM) models, or Generative Pre-trained Transformer (GPT) models. Additionally, other tools such as rule-based systems, summarization algorithms, natural language processing (NLP) models, or abstraction and compression techniques could be used to process the text and generate summaries.